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Record W2156001917 · doi:10.1109/glocom.2007.1012

Performance Analysis of IPTV Traffic in Home Networks

2007· article· en· W2156001917 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsIPTVComputer scienceBurstinessComputer networkBottleneckWireless networkQuality of serviceWirelessTelecommunicationsEmbedded system

Abstract

fetched live from OpenAlex

A heterogeneous wired and wireless network architecture is proposed for in-home IPTV distribution. To identify the bottleneck in the home network and estimate the network capacity, we develop an analytical framework to quantify the maximum number of IPTV connections that can be supported with guaranteed QoS in the wired and multi-hop wireless networks, respectively. We extend the fluid flow model analysis to capture both the burstiness of IPTV sources and the time-varying characteristics of multi-hop wireless channels. Extensive NS-2 simulations with H.264 HDTV sources over wired and multi- hop wireless paths are given, which validate the analysis. The analytical and simulation results provide important guidelines for the planning of future home networks and IPTV systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.211
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations26
Published2007
Admission routes1
Has abstractyes

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